Evidence map›Paper›PMID 42864074›Full record

ArticleNursing in critical care2026

Working With AI and Robotic Systems While Preserving Clinical Judgement, Professional Accountability and Person-Centred Care: Critical Care Nurses' Perspectives.

Tuba Sengul, Dilek Yilmaz Akyaz, Buse Macit Kaplan, Yunus Emre Akyol, Tuğba Cevizci, Melek Demiral, Deema Mahasneh, Noordeen Shoqirat, Holly Kirkland-Kyhn

Abstract read
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Article in Nursing in critical care, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

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No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Tuba SengulKoç University School of Nursing, Istanbul, Türkiye.ORCID https://orcid.org/0000-0002-6253-2016
Dilek Yilmaz AkyazGraduate School of Health Sciences, Koç University, Istanbul, Türkiye.ORCID https://orcid.org/0000-0001-7991-3176
Buse Macit KaplanGraduate School of Health Sciences, Koç University, Istanbul, Türkiye.ORCID https://orcid.org/0009-0001-0697-1401
Yunus Emre AkyolKoç University Hospital, Istanbul, Türkiye.ORCID https://orcid.org/0000-0002-0222-9234
Tuğba CevizciKoç University Hospital, Istanbul, Türkiye.ORCID https://orcid.org/0009-0001-1609-0528
Melek DemiralHaydarpaşa Numune Training and Research Hospital, University of Health Sciences, Istanbul, Türkiye.ORCID https://orcid.org/0000-0001-9827-2669
Deema MahasnehNursing Department, College of Pharmacy and Health Sciences, Ajman University, Ajman, UAE.ORCID https://orcid.org/0000-0003-0019-8101
Noordeen ShoqiratFaculty of Nursing, Mutah University, Karak, Jordan.ORCID https://orcid.org/0000-0002-1567-6869
Holly Kirkland-KyhnBetty Irene Moore School of Nursing, University of California, Davis, USA.ORCID https://orcid.org/0000-0002-9092-9088

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe integration of AI and robotic systems into critical care necessitates examining how ICU nurses preserve clinical judgement, professional accountability and person-centred care while using these technologies.

aimsTo explore ICU nurses' perceptions of AI and robotic systems in critical care, focusing on clinical judgement, trust, responsibility, professional roles and person-centred care. STUDY

designA qualitative descriptive study using scenario-based elicitation was conducted. Data were collected through seven semi-structured focus group discussions (FGDs) with 38 ICU nurses working in general, paediatric and cardiovascular surgery ICUs in two hospitals in Istanbul City. Data were analysed using reflexive thematic analysis, supported by MAXQDA 2024.

findingsFour themes were developed: negotiating trust in AI-supported critical care; preserving human authority, accountability and boundaries; protecting the human core of intensive care nursing; and reimagining AI and robotic systems as supportive partners. ICU nurses evaluated these systems through bedside verification, patient safety, professional responsibility and person-centred care. AI recommendations were useful only when nurses could question, verify, delay or override them according to the patient's current condition. Robotic systems were valuable when they reduced documentation or physical workload, but not when they replaced clinical judgement, emotional presence, reassurance or accountability.

conclusionsICU nurses conceptualised AI and robotic systems as acceptable only when clinically verifiable, professionally bounded and subordinate to human judgement. The findings support a model of AI- and robot-supported ICU care that is responsible, human-led and person-centred. RELEVANCE TO CLINICAL PRACTICE: AI and robotic systems should be implemented in ways that strengthen, rather than replace, nurses' clinical judgement, accountability and bedside presence. Clear protocols are needed to verify AI outputs, define robotic task boundaries, support nurses' authority to question or override recommendations and preserve person-centred care in technologically intensive ICU environments.

Indexed as

Artificial IntelligenceAttitude of Health PersonnelCritical Care NursingJudgmentNursing Staff, HospitalPatient-Centered CareRoboticsAdultFemaleFocus GroupsHumansIntensive Care UnitsMaleMiddle AgedQualitative ResearchSocial Responsibilityartificial intelligenceclinical decision‐makingcritical care nursingperson‐centred carerobotics

Identifiers

PMID42864074
PMCPMC13657853

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.